Data Statistics for Epidemiological Research
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".
Deadline for manuscript submissions: 20 August 2024 | Viewed by 86
Special Issue Editor
2. LASI – Associate Laboratory of Intelligent Systems, Guimarães, Portugal
Interests: artificial intelligence; biostatistics; cognitive psychology; cognitive science and applications; intelligent systems; human–machine interaction; statistics applied to health sciences; statistics applied to quality
Special Issue Information
Dear Colleagues,
Epidemiological research is at the forefront of public health efforts, seeking to comprehend the spread, causes and changes of diseases among populations. Key to this endeavor is the meticulous application of statistical methods to scrutinize intricate datasets, revealing trends, pinpointing risk factors and guiding evidence-based interventions. Acknowledging the pivotal significance of data statistics in propelling epidemiological understanding, we are delighted to unveil a Special Issue devoted to data statistics for epidemiological research. This Special Issue aims to offer a platform for researchers, statisticians, epidemiologists and public health practitioners to present their innovative approaches, methodologies and discoveries in the field of data statistics in epidemiological research. These papers are expected to utilize statistical methodologies in epidemiological research encompassing machine learning and artificial intelligence techniques to aid in uncovering complex relationships within epidemiological data, but are not limited to this field. Effective data visualization and interpretation facilitate the communication of epidemiological findings. Overcoming statistical challenges, integrating big data analytics and addressing ethical considerations are vital for ensuring the integrity and impact of epidemiological research.
Dr. Estela Vilhena
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- big data analytics
- data analysis
- data visualization
- epidemiology
- health outcomes
- machine learning
- public health
- risk factors
- spatial analysis
